Patrick Reiser

Karlsruhe Institute of Technology — Germany

Materials Science · Physical Sciences

14h-index1.4kcitations54works23.02yr avg
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Research Topics

Machine Learning in Materials Science(25), Organic Electronics and Photovoltaics(15), Conducting polymers and applications(7), Advanced Graph Neural Networks(7), Computational Drug Discovery Methods(6)

Publications54 total

Learning Potential Energy Surfaces of Hydrogen Atom Transfer Reactions in Peptides
arXiv (Cornell University)·2025Open Access
Tuning the Transparency and Exciton Transition of D‐π‐A‐π‐D Type Small Molecules
Chemistry - A European Journal·2025· 1 citedOpen Access
Inverse design workflow discovers hole-transport materials tailored for perovskite solar cells
Science·2024· 128 cited
Discovering one molecule out of a million: inverse design of molecular hole transporting semiconductors tailored for perovskite solar cells
arXiv (Cornell University)·2024Open Access
JARVIS-Leaderboard: a large scale benchmark of materials design methods
npj Computational Materials·2024· 38 citedOpen Access
Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins
2024Open Access
Author response for "Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins"
2024
Connectivity optimized nested line graph networks for crystal structures
Digital Discovery·2024· 32 citedOpen Access
Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins
Chemical Science·2024· 8 citedOpen Access
Author response for "Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins"
2023
Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins
2023Open Access
Accurate GW frontier orbital energies of 134 kilo molecules
Scientific Data·2023· 14 citedOpen Access
Interpretable delta-learning of GW quasiparticle energies from GGA-DFT
Machine Learning Science and Technology·2023· 4 citedOpen Access
Integrated System Built for Small-Molecule Semiconductors via High-Throughput Approaches
Journal of the American Chemical Society·2023· 24 citedOpen Access
OligoHydrogelArray (OHA) for Parallelized Solid‐Phase Extraction of Oligonucleotides
Advanced Materials Interfaces·2023· 3 citedOpen Access
Modeling Charge Transport in Organic Semiconductors Using Neural Network Based Hamiltonians and Forces
Journal of Chemical Theory and Computation·2023· 7 cited
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods
arXiv (Cornell University)·2023· 4 citedOpen Access
High‐Throughput Synthesis and Machine Learning Assisted Design of Photodegradable Hydrogels
Small Methods·2023· 33 citedOpen Access
Neural networks trained on synthetically generated crystals can extract structural information from ICSD powder X-ray diffractograms
arXiv (Cornell University)·2023· 1 citedOpen Access
Lattice Metamaterials with Mesoscale Motifs: Exploration of Property Charts by Bayesian Optimization
Advanced Engineering Materials·2023· 9 citedOpen Access
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Frequent Co-authors

Pascal Friederich(38), Eric Mankel(8), Luca Torresi(7), Robert Lovrinčić(7), Henrik Schopmans(6), Wolfgang Kowalsky(6), Annemarie Pucci(6), Frauke Gräter(6), André Eberhard(5), Sebastian Beck(5), Wolfram Jaegermann(5), Kai Riedmiller(5), Elizaveta Bobkova(5), Kiril Maltsev(5), Ganna Gryn’ova(5), Juan S. Rocha‐Ortiz(4), Anastasia Barabash(4), Jens Hauch(4), Gerardo Hernandez‐Sosa(4), Lars Müller(4)